Scene Text Detection and Recognition is a problem of reading letters from everyday landscape images. Recently, STR research using deep learning models has been actively conducted for various applications. However, STR still has many challenges to over...
Scene Text Detection and Recognition is a problem of reading letters from everyday landscape images. Recently, STR research using deep learning models has been actively conducted for various applications. However, STR still has many challenges to overcome due to the complexity in image contents, which is much more challenging compared to recognizing letters in paper documents. In addition, the STR performance appears good for foreign characters such as English or Chinese, but poor for Korean. In this paper, we develop a model suitable for the Korean environment through the real world Korean scene text dataset. We measure the performance of various configurations of networks to find suitable network structure.